mirror of
https://github.com/outbackdingo/optimclaw.git
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58a3eb1366
* fix(worker): prevent orphaned tool_results and fix parallel merging Two fixes for tool result handling in the Worker: 1. Preserve reasoning text from select_tools() in the RespondResult content field so it appears in the assistant_with_tool_calls message pushed by execute_tool_calls. Without this, the LLM's reasoning context was lost when using the select_tools path. 2. Merge consecutive tool_result messages into a single User message in rig_adapter's convert_messages(). When parallel tools execute, each produces a separate ChatMessage with role: Tool. Without merging, these become consecutive User messages which Anthropic rejects. Now consecutive tool results are merged into one User message with multiple ToolResult content items. Includes regression tests for both fixes. Co-Authored-By: Claude Opus 4.6 <[email protected]> * fix(worker): use find_map for first non-empty reasoning extraction The previous code only checked the first ToolSelection's reasoning, missing cases where the first selection has empty reasoning but subsequent ones do not. Switch to find_map to get the first non-empty reasoning across all selections. Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> --------- Co-authored-by: Claude Opus 4.6 <[email protected]>
1364 lines
50 KiB
Rust
1364 lines
50 KiB
Rust
//! Generic adapter that bridges rig-core's `CompletionModel` trait to IronClaw's `LlmProvider`.
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//!
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//! This lets us use any rig-core provider (OpenAI, Anthropic, Ollama, etc.) as an
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//! `Arc<dyn LlmProvider>` without changing any of the agent, reasoning, or tool code.
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use crate::llm::config::CacheRetention;
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use async_trait::async_trait;
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use rig::OneOrMany;
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use rig::completion::{
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AssistantContent, CompletionModel, CompletionRequest as RigRequest,
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ToolDefinition as RigToolDefinition, Usage as RigUsage,
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};
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use rig::message::{
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DocumentSourceKind, Image, ImageMediaType, Message as RigMessage, MimeType,
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ToolChoice as RigToolChoice, ToolFunction, ToolResult as RigToolResult, ToolResultContent,
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UserContent,
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};
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use rust_decimal::Decimal;
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use rust_decimal_macros::dec;
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use serde::Serialize;
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use serde::de::DeserializeOwned;
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use serde_json::Value as JsonValue;
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use std::collections::HashSet;
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use crate::llm::costs;
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use crate::llm::error::LlmError;
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use crate::llm::provider::{
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ChatMessage, CompletionRequest, CompletionResponse, FinishReason, LlmProvider,
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ToolCall as IronToolCall, ToolCompletionRequest, ToolCompletionResponse,
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ToolDefinition as IronToolDefinition, strip_unsupported_completion_params,
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strip_unsupported_tool_params,
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};
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/// Adapter that wraps a rig-core `CompletionModel` and implements `LlmProvider`.
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pub struct RigAdapter<M: CompletionModel> {
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model: M,
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model_name: String,
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input_cost: Decimal,
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output_cost: Decimal,
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/// Prompt cache retention policy (Anthropic only).
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/// When not `CacheRetention::None`, injects top-level `cache_control`
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/// via `additional_params` for Anthropic automatic caching. Also controls
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/// the cost multiplier for cache-creation tokens.
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cache_retention: CacheRetention,
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/// Parameter names that this provider does not support (e.g., `"temperature"`).
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/// These are stripped from requests before sending to avoid 400 errors.
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unsupported_params: HashSet<String>,
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}
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impl<M: CompletionModel> RigAdapter<M> {
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/// Create a new adapter wrapping the given rig-core model.
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pub fn new(model: M, model_name: impl Into<String>) -> Self {
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let name = model_name.into();
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let (input_cost, output_cost) =
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costs::model_cost(&name).unwrap_or_else(costs::default_cost);
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Self {
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model,
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model_name: name,
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input_cost,
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output_cost,
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cache_retention: CacheRetention::None,
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unsupported_params: HashSet::new(),
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}
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}
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/// Set Anthropic prompt cache retention policy.
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///
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/// Controls both cache injection and cost tracking:
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/// - `None` — no caching, no surcharge (1.0×).
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/// - `Short` — 5-minute TTL via `{"type": "ephemeral"}`, 1.25× write surcharge.
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/// - `Long` — 1-hour TTL via `{"type": "ephemeral", "ttl": "1h"}`, 2.0× write surcharge.
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///
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/// Cache injection uses Anthropic's **automatic caching** — a top-level
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/// `cache_control` field in `additional_params` that gets `#[serde(flatten)]`'d
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/// into the request body by rig-core.
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///
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/// If the configured model does not support caching (e.g. claude-2),
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/// a warning is logged once at construction and caching is disabled.
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pub fn with_cache_retention(mut self, retention: CacheRetention) -> Self {
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if retention != CacheRetention::None && !supports_prompt_cache(&self.model_name) {
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tracing::warn!(
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model = %self.model_name,
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"Prompt caching requested but model does not support it; disabling"
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);
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self.cache_retention = CacheRetention::None;
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} else {
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self.cache_retention = retention;
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}
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self
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}
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/// Set the list of unsupported parameter names for this provider.
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///
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/// Parameters in this set are stripped from requests before sending.
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/// Supported parameter names: `"temperature"`, `"max_tokens"`, `"stop_sequences"`.
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pub fn with_unsupported_params(mut self, params: Vec<String>) -> Self {
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self.unsupported_params = params.into_iter().collect();
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self
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}
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/// Strip unsupported fields from a `CompletionRequest` in place.
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fn strip_unsupported_completion_params(&self, req: &mut CompletionRequest) {
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strip_unsupported_completion_params(&self.unsupported_params, req);
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}
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/// Strip unsupported fields from a `ToolCompletionRequest` in place.
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fn strip_unsupported_tool_params(&self, req: &mut ToolCompletionRequest) {
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strip_unsupported_tool_params(&self.unsupported_params, req);
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}
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}
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// -- Type conversion helpers --
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/// Normalize a JSON Schema for OpenAI strict mode compliance.
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///
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/// OpenAI strict function calling requires:
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/// - Every object must have `"additionalProperties": false`
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/// - `"required"` must list ALL property keys
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/// - Optional fields use `"type": ["<original>", "null"]` instead of being omitted from `required`
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/// - Nested objects and array items are recursively normalized
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///
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/// This is applied as a clone-and-transform at the provider boundary so the
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/// original tool definitions remain unchanged for other providers.
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fn normalize_schema_strict(schema: &JsonValue) -> JsonValue {
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let mut schema = schema.clone();
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normalize_schema_recursive(&mut schema);
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schema
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}
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fn normalize_schema_recursive(schema: &mut JsonValue) {
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let obj = match schema.as_object_mut() {
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Some(o) => o,
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None => return,
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};
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// Recurse into combinators: anyOf, oneOf, allOf
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for key in &["anyOf", "oneOf", "allOf"] {
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if let Some(JsonValue::Array(variants)) = obj.get_mut(*key) {
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for variant in variants.iter_mut() {
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normalize_schema_recursive(variant);
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}
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}
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}
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// Recurse into array items
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if let Some(items) = obj.get_mut("items") {
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normalize_schema_recursive(items);
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}
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// Recurse into `not`, `if`, `then`, `else`
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for key in &["not", "if", "then", "else"] {
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if let Some(sub) = obj.get_mut(*key) {
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normalize_schema_recursive(sub);
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}
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}
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// Only apply object-level normalization if this schema has "properties"
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// (explicit object schema) or type == "object"
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let is_object = obj
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.get("type")
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.and_then(|t| t.as_str())
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.map(|t| t == "object")
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.unwrap_or(false);
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let has_properties = obj.contains_key("properties");
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if !is_object && !has_properties {
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return;
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}
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// Ensure "type": "object" is present
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if !obj.contains_key("type") && has_properties {
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obj.insert("type".to_string(), JsonValue::String("object".to_string()));
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}
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// Force additionalProperties: false (overwrite any existing value)
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obj.insert("additionalProperties".to_string(), JsonValue::Bool(false));
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// Ensure "properties" exists
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if !obj.contains_key("properties") {
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obj.insert(
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"properties".to_string(),
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JsonValue::Object(serde_json::Map::new()),
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);
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}
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// Collect current required set
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let current_required: std::collections::HashSet<String> = obj
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.get("required")
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.and_then(|r| r.as_array())
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.map(|arr| {
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arr.iter()
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.filter_map(|v| v.as_str().map(String::from))
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.collect()
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})
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.unwrap_or_default();
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// Get all property keys (sorted for deterministic output)
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let all_keys: Vec<String> = obj
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.get("properties")
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.and_then(|p| p.as_object())
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.map(|props| {
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let mut keys: Vec<String> = props.keys().cloned().collect();
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keys.sort();
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keys
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})
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.unwrap_or_default();
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// For properties NOT in the original required list, make them nullable
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if let Some(JsonValue::Object(props)) = obj.get_mut("properties") {
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for key in &all_keys {
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// Recurse into each property's schema FIRST (before make_nullable,
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// which may change the type to an array and prevent object detection)
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if let Some(prop_schema) = props.get_mut(key) {
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normalize_schema_recursive(prop_schema);
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}
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// Then make originally-optional properties nullable
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if !current_required.contains(key)
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&& let Some(prop_schema) = props.get_mut(key)
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{
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make_nullable(prop_schema);
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}
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}
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}
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// Set required to ALL property keys
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let required_value: Vec<JsonValue> = all_keys.into_iter().map(JsonValue::String).collect();
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obj.insert("required".to_string(), JsonValue::Array(required_value));
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}
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/// Make a property schema nullable for OpenAI strict mode.
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///
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/// If it has a simple `"type": "<T>"`, converts to `"type": ["<T>", "null"]`.
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/// If it already has an array type, adds "null" if not present.
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/// Otherwise, wraps with `anyOf: [<existing>, {"type": "null"}]`.
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fn make_nullable(schema: &mut JsonValue) {
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let obj = match schema.as_object_mut() {
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Some(o) => o,
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None => return,
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};
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if let Some(type_val) = obj.get("type").cloned() {
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match type_val {
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// "type": "string" → "type": ["string", "null"]
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JsonValue::String(ref t) if t != "null" => {
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obj.insert("type".to_string(), serde_json::json!([t, "null"]));
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}
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// "type": ["string", "integer"] → add "null" if missing
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JsonValue::Array(ref arr) => {
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let has_null = arr.iter().any(|v| v.as_str() == Some("null"));
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if !has_null {
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let mut new_arr = arr.clone();
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new_arr.push(JsonValue::String("null".to_string()));
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obj.insert("type".to_string(), JsonValue::Array(new_arr));
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}
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}
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_ => {}
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}
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} else {
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// No "type" key — wrap with anyOf including null
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// (handles enum-only, $ref, or combinator schemas)
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let existing = JsonValue::Object(obj.clone());
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obj.clear();
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obj.insert(
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"anyOf".to_string(),
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serde_json::json!([existing, {"type": "null"}]),
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);
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}
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}
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/// Convert IronClaw messages to rig-core format.
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///
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/// Returns `(preamble, chat_history)` where preamble is extracted from
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/// any System message and chat_history contains the rest.
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fn convert_messages(messages: &[ChatMessage]) -> (Option<String>, Vec<RigMessage>) {
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let mut preamble: Option<String> = None;
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let mut history = Vec::new();
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for msg in messages {
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match msg.role {
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crate::llm::Role::System => {
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// Concatenate system messages into preamble
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match preamble {
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Some(ref mut p) => {
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p.push('\n');
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p.push_str(&msg.content);
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}
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None => preamble = Some(msg.content.clone()),
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}
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}
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crate::llm::Role::User => {
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if msg.content_parts.is_empty() {
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history.push(RigMessage::user(&msg.content));
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} else {
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// Build multimodal user message with text + image parts
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let mut contents: Vec<UserContent> = vec![UserContent::text(&msg.content)];
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for part in &msg.content_parts {
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if let crate::llm::ContentPart::ImageUrl { image_url } = part {
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// Parse data: URL for base64 images, or use raw URL
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let image = if let Some(rest) = image_url.url.strip_prefix("data:") {
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// Format: data:<mime>;base64,<data>
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let (mime, b64) =
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rest.split_once(";base64,").unwrap_or(("image/jpeg", rest));
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Image {
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data: DocumentSourceKind::base64(b64),
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media_type: ImageMediaType::from_mime_type(mime),
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detail: None,
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additional_params: None,
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}
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} else {
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Image {
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data: DocumentSourceKind::url(&image_url.url),
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media_type: None,
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detail: None,
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additional_params: None,
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}
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};
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contents.push(UserContent::Image(image));
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}
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}
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if let Ok(many) = OneOrMany::many(contents) {
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history.push(RigMessage::User { content: many });
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} else {
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history.push(RigMessage::user(&msg.content));
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}
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}
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}
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crate::llm::Role::Assistant => {
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if let Some(ref tool_calls) = msg.tool_calls {
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// Assistant message with tool calls
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let mut contents: Vec<AssistantContent> = Vec::new();
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if !msg.content.is_empty() {
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contents.push(AssistantContent::text(&msg.content));
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}
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for (idx, tc) in tool_calls.iter().enumerate() {
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let tool_call_id =
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normalized_tool_call_id(Some(tc.id.as_str()), history.len() + idx);
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contents.push(AssistantContent::ToolCall(
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rig::message::ToolCall::new(
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tool_call_id.clone(),
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ToolFunction::new(tc.name.clone(), tc.arguments.clone()),
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)
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.with_call_id(tool_call_id),
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));
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}
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if let Ok(many) = OneOrMany::many(contents) {
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history.push(RigMessage::Assistant {
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id: None,
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content: many,
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});
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} else {
|
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// Shouldn't happen but fall back to text
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history.push(RigMessage::assistant(&msg.content));
|
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}
|
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} else {
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history.push(RigMessage::assistant(&msg.content));
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}
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}
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crate::llm::Role::Tool => {
|
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// Tool result message: wrap as User { ToolResult }.
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// Merge consecutive tool results into a single User message
|
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// so the API sees one multi-result message instead of
|
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// multiple consecutive User messages (which Anthropic rejects).
|
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let tool_id = normalized_tool_call_id(msg.tool_call_id.as_deref(), history.len());
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let tool_result = UserContent::ToolResult(RigToolResult {
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id: tool_id.clone(),
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call_id: Some(tool_id),
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content: OneOrMany::one(ToolResultContent::text(&msg.content)),
|
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});
|
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|
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let should_merge = matches!(
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history.last(),
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Some(RigMessage::User { content }) if content.iter().all(|c| matches!(c, UserContent::ToolResult(_)))
|
||
);
|
||
|
||
if should_merge {
|
||
if let Some(RigMessage::User { content }) = history.last_mut() {
|
||
content.push(tool_result);
|
||
}
|
||
} else {
|
||
history.push(RigMessage::User {
|
||
content: OneOrMany::one(tool_result),
|
||
});
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
(preamble, history)
|
||
}
|
||
|
||
/// Responses-style providers require a non-empty tool call ID.
|
||
fn normalized_tool_call_id(raw: Option<&str>, seed: usize) -> String {
|
||
match raw.map(str::trim).filter(|id| !id.is_empty()) {
|
||
Some(id) => id.to_string(),
|
||
None => format!("generated_tool_call_{seed}"),
|
||
}
|
||
}
|
||
|
||
/// Convert IronClaw tool definitions to rig-core format.
|
||
///
|
||
/// Applies OpenAI strict-mode schema normalization to ensure all tool
|
||
/// parameter schemas comply with OpenAI's function calling requirements.
|
||
fn convert_tools(tools: &[IronToolDefinition]) -> Vec<RigToolDefinition> {
|
||
tools
|
||
.iter()
|
||
.map(|t| RigToolDefinition {
|
||
name: t.name.clone(),
|
||
description: t.description.clone(),
|
||
parameters: normalize_schema_strict(&t.parameters),
|
||
})
|
||
.collect()
|
||
}
|
||
|
||
/// Convert IronClaw tool_choice string to rig-core ToolChoice.
|
||
fn convert_tool_choice(choice: Option<&str>) -> Option<RigToolChoice> {
|
||
match choice.map(|s| s.to_lowercase()).as_deref() {
|
||
Some("auto") => Some(RigToolChoice::Auto),
|
||
Some("required") => Some(RigToolChoice::Required),
|
||
Some("none") => Some(RigToolChoice::None),
|
||
_ => None,
|
||
}
|
||
}
|
||
|
||
/// Extract text and tool calls from a rig-core completion response.
|
||
fn extract_response(
|
||
choice: &OneOrMany<AssistantContent>,
|
||
_usage: &RigUsage,
|
||
) -> (Option<String>, Vec<IronToolCall>, FinishReason) {
|
||
let mut text_parts: Vec<String> = Vec::new();
|
||
let mut tool_calls: Vec<IronToolCall> = Vec::new();
|
||
|
||
for content in choice.iter() {
|
||
match content {
|
||
AssistantContent::Text(t) => {
|
||
if !t.text.is_empty() {
|
||
text_parts.push(t.text.clone());
|
||
}
|
||
}
|
||
AssistantContent::ToolCall(tc) => {
|
||
tool_calls.push(IronToolCall {
|
||
id: tc.id.clone(),
|
||
name: tc.function.name.clone(),
|
||
arguments: tc.function.arguments.clone(),
|
||
});
|
||
}
|
||
// Reasoning and Image variants are not mapped to IronClaw types
|
||
_ => {}
|
||
}
|
||
}
|
||
|
||
let text = if text_parts.is_empty() {
|
||
None
|
||
} else {
|
||
Some(text_parts.join(""))
|
||
};
|
||
|
||
let finish = if !tool_calls.is_empty() {
|
||
FinishReason::ToolUse
|
||
} else {
|
||
FinishReason::Stop
|
||
};
|
||
|
||
(text, tool_calls, finish)
|
||
}
|
||
|
||
/// Saturate u64 to u32 for token counts.
|
||
fn saturate_u32(val: u64) -> u32 {
|
||
val.min(u32::MAX as u64) as u32
|
||
}
|
||
|
||
/// Returns `true` if the model supports Anthropic prompt caching.
|
||
///
|
||
/// Per Anthropic docs, only Claude 3+ models support prompt caching.
|
||
/// Unsupported: claude-2, claude-2.1, claude-instant-*.
|
||
fn supports_prompt_cache(name: &str) -> bool {
|
||
let lower = name.to_lowercase();
|
||
// Strip optional provider prefix (e.g. "anthropic/claude-...")
|
||
let model = lower.strip_prefix("anthropic/").unwrap_or(&lower);
|
||
// Only Claude 3+ families support prompt caching
|
||
model.starts_with("claude-3")
|
||
|| model.starts_with("claude-4")
|
||
|| model.starts_with("claude-sonnet")
|
||
|| model.starts_with("claude-opus")
|
||
|| model.starts_with("claude-haiku")
|
||
}
|
||
|
||
/// Extract `cache_creation_input_tokens` from the raw provider response.
|
||
///
|
||
/// Rig-core's unified `Usage` does not surface this field, but Anthropic's raw
|
||
/// response includes it at `usage.cache_creation_input_tokens`. We serialize the
|
||
/// raw response to JSON and attempt to read the value.
|
||
fn extract_cache_creation<T: Serialize>(raw: &T) -> u32 {
|
||
serde_json::to_value(raw)
|
||
.ok()
|
||
.and_then(|v| v.get("usage")?.get("cache_creation_input_tokens")?.as_u64())
|
||
.map(|n| n.min(u32::MAX as u64) as u32)
|
||
.unwrap_or(0)
|
||
}
|
||
|
||
/// Build a rig-core CompletionRequest from our internal types.
|
||
///
|
||
/// When `cache_retention` is not `None`, injects a top-level `cache_control`
|
||
/// field via `additional_params`. Rig-core's `AnthropicCompletionRequest`
|
||
/// uses `#[serde(flatten)]` on `additional_params`, so the field lands at
|
||
/// the request root — which is exactly what Anthropic's **automatic caching**
|
||
/// expects. The API auto-places the cache breakpoint at the last cacheable
|
||
/// block and moves it forward as conversations grow.
|
||
#[allow(clippy::too_many_arguments)]
|
||
fn build_rig_request(
|
||
preamble: Option<String>,
|
||
mut history: Vec<RigMessage>,
|
||
tools: Vec<RigToolDefinition>,
|
||
tool_choice: Option<RigToolChoice>,
|
||
temperature: Option<f32>,
|
||
max_tokens: Option<u32>,
|
||
cache_retention: CacheRetention,
|
||
) -> Result<RigRequest, LlmError> {
|
||
// rig-core requires at least one message in chat_history
|
||
if history.is_empty() {
|
||
history.push(RigMessage::user("Hello"));
|
||
}
|
||
|
||
let chat_history = OneOrMany::many(history).map_err(|e| LlmError::RequestFailed {
|
||
provider: "rig".to_string(),
|
||
reason: format!("Failed to build chat history: {}", e),
|
||
})?;
|
||
|
||
// Inject top-level cache_control for Anthropic automatic prompt caching.
|
||
let additional_params = match cache_retention {
|
||
CacheRetention::None => None,
|
||
CacheRetention::Short => Some(serde_json::json!({
|
||
"cache_control": {"type": "ephemeral"}
|
||
})),
|
||
CacheRetention::Long => Some(serde_json::json!({
|
||
"cache_control": {"type": "ephemeral", "ttl": "1h"}
|
||
})),
|
||
};
|
||
|
||
Ok(RigRequest {
|
||
preamble,
|
||
chat_history,
|
||
documents: Vec::new(),
|
||
tools,
|
||
temperature: temperature.map(|t| t as f64),
|
||
max_tokens: max_tokens.map(|t| t as u64),
|
||
tool_choice,
|
||
additional_params,
|
||
})
|
||
}
|
||
|
||
#[async_trait]
|
||
impl<M> LlmProvider for RigAdapter<M>
|
||
where
|
||
M: CompletionModel + Send + Sync + 'static,
|
||
M::Response: Send + Sync + Serialize + DeserializeOwned,
|
||
{
|
||
fn model_name(&self) -> &str {
|
||
&self.model_name
|
||
}
|
||
|
||
fn cost_per_token(&self) -> (Decimal, Decimal) {
|
||
(self.input_cost, self.output_cost)
|
||
}
|
||
|
||
fn cache_write_multiplier(&self) -> Decimal {
|
||
match self.cache_retention {
|
||
CacheRetention::None => Decimal::ONE,
|
||
CacheRetention::Short => Decimal::new(125, 2), // 1.25× (125% of input rate)
|
||
CacheRetention::Long => Decimal::TWO, // 2.0× (200% of input rate)
|
||
}
|
||
}
|
||
|
||
fn cache_read_discount(&self) -> Decimal {
|
||
if self.cache_retention != CacheRetention::None {
|
||
dec!(10) // Anthropic: 90% discount (cost = input_rate / 10)
|
||
} else {
|
||
Decimal::ONE
|
||
}
|
||
}
|
||
|
||
async fn complete(
|
||
&self,
|
||
mut request: CompletionRequest,
|
||
) -> Result<CompletionResponse, LlmError> {
|
||
if let Some(requested_model) = request.model.as_deref()
|
||
&& requested_model != self.model_name.as_str()
|
||
{
|
||
tracing::warn!(
|
||
requested_model = requested_model,
|
||
active_model = %self.model_name,
|
||
"Per-request model override is not supported for this provider; using configured model"
|
||
);
|
||
}
|
||
|
||
self.strip_unsupported_completion_params(&mut request);
|
||
|
||
let mut messages = request.messages;
|
||
crate::llm::provider::sanitize_tool_messages(&mut messages);
|
||
let (preamble, history) = convert_messages(&messages);
|
||
|
||
let rig_req = build_rig_request(
|
||
preamble,
|
||
history,
|
||
Vec::new(),
|
||
None,
|
||
request.temperature,
|
||
request.max_tokens,
|
||
self.cache_retention,
|
||
)?;
|
||
|
||
let response =
|
||
self.model
|
||
.completion(rig_req)
|
||
.await
|
||
.map_err(|e| LlmError::RequestFailed {
|
||
provider: self.model_name.clone(),
|
||
reason: e.to_string(),
|
||
})?;
|
||
|
||
let (text, _tool_calls, finish) = extract_response(&response.choice, &response.usage);
|
||
|
||
let resp = CompletionResponse {
|
||
content: text.unwrap_or_default(),
|
||
input_tokens: saturate_u32(response.usage.input_tokens),
|
||
output_tokens: saturate_u32(response.usage.output_tokens),
|
||
finish_reason: finish,
|
||
cache_read_input_tokens: saturate_u32(response.usage.cached_input_tokens),
|
||
cache_creation_input_tokens: extract_cache_creation(&response.raw_response),
|
||
};
|
||
|
||
if resp.cache_read_input_tokens > 0 {
|
||
tracing::debug!(
|
||
model = %self.model_name,
|
||
input = resp.input_tokens,
|
||
output = resp.output_tokens,
|
||
cache_read = resp.cache_read_input_tokens,
|
||
"prompt cache hit",
|
||
);
|
||
}
|
||
|
||
Ok(resp)
|
||
}
|
||
|
||
async fn complete_with_tools(
|
||
&self,
|
||
mut request: ToolCompletionRequest,
|
||
) -> Result<ToolCompletionResponse, LlmError> {
|
||
if let Some(requested_model) = request.model.as_deref()
|
||
&& requested_model != self.model_name.as_str()
|
||
{
|
||
tracing::warn!(
|
||
requested_model = requested_model,
|
||
active_model = %self.model_name,
|
||
"Per-request model override is not supported for this provider; using configured model"
|
||
);
|
||
}
|
||
|
||
self.strip_unsupported_tool_params(&mut request);
|
||
|
||
let known_tool_names: HashSet<String> =
|
||
request.tools.iter().map(|t| t.name.clone()).collect();
|
||
|
||
let mut messages = request.messages;
|
||
crate::llm::provider::sanitize_tool_messages(&mut messages);
|
||
let (preamble, history) = convert_messages(&messages);
|
||
let tools = convert_tools(&request.tools);
|
||
let tool_choice = convert_tool_choice(request.tool_choice.as_deref());
|
||
|
||
let rig_req = build_rig_request(
|
||
preamble,
|
||
history,
|
||
tools,
|
||
tool_choice,
|
||
request.temperature,
|
||
request.max_tokens,
|
||
self.cache_retention,
|
||
)?;
|
||
|
||
let response =
|
||
self.model
|
||
.completion(rig_req)
|
||
.await
|
||
.map_err(|e| LlmError::RequestFailed {
|
||
provider: self.model_name.clone(),
|
||
reason: e.to_string(),
|
||
})?;
|
||
|
||
let (text, mut tool_calls, finish) = extract_response(&response.choice, &response.usage);
|
||
|
||
// Normalize tool call names: some proxies prepend "proxy_" prefixes.
|
||
for tc in &mut tool_calls {
|
||
let normalized = normalize_tool_name(&tc.name, &known_tool_names);
|
||
if normalized != tc.name {
|
||
tracing::debug!(
|
||
original = %tc.name,
|
||
normalized = %normalized,
|
||
"Normalized tool call name from provider",
|
||
);
|
||
tc.name = normalized;
|
||
}
|
||
}
|
||
|
||
let resp = ToolCompletionResponse {
|
||
content: text,
|
||
tool_calls,
|
||
input_tokens: saturate_u32(response.usage.input_tokens),
|
||
output_tokens: saturate_u32(response.usage.output_tokens),
|
||
finish_reason: finish,
|
||
cache_read_input_tokens: saturate_u32(response.usage.cached_input_tokens),
|
||
cache_creation_input_tokens: extract_cache_creation(&response.raw_response),
|
||
};
|
||
|
||
if resp.cache_read_input_tokens > 0 {
|
||
tracing::debug!(
|
||
model = %self.model_name,
|
||
input = resp.input_tokens,
|
||
output = resp.output_tokens,
|
||
cache_read = resp.cache_read_input_tokens,
|
||
"prompt cache hit",
|
||
);
|
||
}
|
||
|
||
Ok(resp)
|
||
}
|
||
|
||
fn active_model_name(&self) -> String {
|
||
self.model_name.clone()
|
||
}
|
||
|
||
fn effective_model_name(&self, _requested_model: Option<&str>) -> String {
|
||
self.active_model_name()
|
||
}
|
||
|
||
fn set_model(&self, _model: &str) -> Result<(), LlmError> {
|
||
// rig-core models are baked at construction time.
|
||
// Switching requires creating a new adapter.
|
||
Err(LlmError::RequestFailed {
|
||
provider: self.model_name.clone(),
|
||
reason: "Runtime model switching not supported for rig-core providers. \
|
||
Restart with a different model configured."
|
||
.to_string(),
|
||
})
|
||
}
|
||
}
|
||
|
||
/// Normalize a tool call name returned by an OpenAI-compatible provider.
|
||
///
|
||
/// Some proxies (e.g. VibeProxy) prepend `proxy_` to tool names.
|
||
/// If the returned name doesn't match any known tool but stripping a
|
||
/// `proxy_` prefix yields a match, use the stripped version.
|
||
fn normalize_tool_name(name: &str, known_tools: &HashSet<String>) -> String {
|
||
if known_tools.contains(name) {
|
||
return name.to_string();
|
||
}
|
||
|
||
if let Some(stripped) = name.strip_prefix("proxy_")
|
||
&& known_tools.contains(stripped)
|
||
{
|
||
return stripped.to_string();
|
||
}
|
||
|
||
name.to_string()
|
||
}
|
||
|
||
#[cfg(test)]
|
||
mod tests {
|
||
use super::*;
|
||
|
||
#[test]
|
||
fn test_convert_messages_system_to_preamble() {
|
||
let messages = vec![
|
||
ChatMessage::system("You are a helpful assistant."),
|
||
ChatMessage::user("Hello"),
|
||
];
|
||
let (preamble, history) = convert_messages(&messages);
|
||
assert_eq!(preamble, Some("You are a helpful assistant.".to_string()));
|
||
assert_eq!(history.len(), 1);
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_messages_multiple_systems_concatenated() {
|
||
let messages = vec![
|
||
ChatMessage::system("System 1"),
|
||
ChatMessage::system("System 2"),
|
||
ChatMessage::user("Hi"),
|
||
];
|
||
let (preamble, history) = convert_messages(&messages);
|
||
assert_eq!(preamble, Some("System 1\nSystem 2".to_string()));
|
||
assert_eq!(history.len(), 1);
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_messages_tool_result() {
|
||
let messages = vec![ChatMessage::tool_result(
|
||
"call_123",
|
||
"search",
|
||
"result text",
|
||
)];
|
||
let (preamble, history) = convert_messages(&messages);
|
||
assert!(preamble.is_none());
|
||
assert_eq!(history.len(), 1);
|
||
// Tool results become User messages in rig-core
|
||
match &history[0] {
|
||
RigMessage::User { content } => match content.first() {
|
||
UserContent::ToolResult(r) => {
|
||
assert_eq!(r.id, "call_123");
|
||
assert_eq!(r.call_id.as_deref(), Some("call_123"));
|
||
}
|
||
other => panic!("Expected tool result content, got: {:?}", other),
|
||
},
|
||
other => panic!("Expected User message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_messages_assistant_with_tool_calls() {
|
||
let tc = IronToolCall {
|
||
id: "call_1".to_string(),
|
||
name: "search".to_string(),
|
||
arguments: serde_json::json!({"query": "test"}),
|
||
};
|
||
let msg = ChatMessage::assistant_with_tool_calls(Some("thinking".to_string()), vec![tc]);
|
||
let messages = vec![msg];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
assert_eq!(history.len(), 1);
|
||
match &history[0] {
|
||
RigMessage::Assistant { content, .. } => {
|
||
// Should have both text and tool call
|
||
assert!(content.iter().count() >= 2);
|
||
for item in content.iter() {
|
||
if let AssistantContent::ToolCall(tc) = item {
|
||
assert_eq!(tc.call_id.as_deref(), Some("call_1"));
|
||
}
|
||
}
|
||
}
|
||
other => panic!("Expected Assistant message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_messages_tool_result_without_id_gets_fallback() {
|
||
let messages = vec![ChatMessage {
|
||
role: crate::llm::Role::Tool,
|
||
content: "result text".to_string(),
|
||
content_parts: Vec::new(),
|
||
tool_call_id: None,
|
||
name: Some("search".to_string()),
|
||
tool_calls: None,
|
||
}];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
match &history[0] {
|
||
RigMessage::User { content } => match content.first() {
|
||
UserContent::ToolResult(r) => {
|
||
assert!(r.id.starts_with("generated_tool_call_"));
|
||
assert_eq!(r.call_id.as_deref(), Some(r.id.as_str()));
|
||
}
|
||
other => panic!("Expected tool result content, got: {:?}", other),
|
||
},
|
||
other => panic!("Expected User message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_tools() {
|
||
let tools = vec![IronToolDefinition {
|
||
name: "search".to_string(),
|
||
description: "Search the web".to_string(),
|
||
parameters: serde_json::json!({
|
||
"type": "object",
|
||
"properties": {
|
||
"query": {"type": "string"}
|
||
}
|
||
}),
|
||
}];
|
||
let rig_tools = convert_tools(&tools);
|
||
assert_eq!(rig_tools.len(), 1);
|
||
assert_eq!(rig_tools[0].name, "search");
|
||
assert_eq!(rig_tools[0].description, "Search the web");
|
||
}
|
||
|
||
#[test]
|
||
fn test_convert_tool_choice() {
|
||
assert!(matches!(
|
||
convert_tool_choice(Some("auto")),
|
||
Some(RigToolChoice::Auto)
|
||
));
|
||
assert!(matches!(
|
||
convert_tool_choice(Some("required")),
|
||
Some(RigToolChoice::Required)
|
||
));
|
||
assert!(matches!(
|
||
convert_tool_choice(Some("none")),
|
||
Some(RigToolChoice::None)
|
||
));
|
||
assert!(matches!(
|
||
convert_tool_choice(Some("AUTO")),
|
||
Some(RigToolChoice::Auto)
|
||
));
|
||
assert!(convert_tool_choice(None).is_none());
|
||
assert!(convert_tool_choice(Some("unknown")).is_none());
|
||
}
|
||
|
||
#[test]
|
||
fn test_extract_response_text_only() {
|
||
let content = OneOrMany::one(AssistantContent::text("Hello world"));
|
||
let usage = RigUsage::new();
|
||
let (text, calls, finish) = extract_response(&content, &usage);
|
||
assert_eq!(text, Some("Hello world".to_string()));
|
||
assert!(calls.is_empty());
|
||
assert_eq!(finish, FinishReason::Stop);
|
||
}
|
||
|
||
#[test]
|
||
fn test_extract_response_tool_call() {
|
||
let tc = AssistantContent::tool_call("call_1", "search", serde_json::json!({"q": "test"}));
|
||
let content = OneOrMany::one(tc);
|
||
let usage = RigUsage::new();
|
||
let (text, calls, finish) = extract_response(&content, &usage);
|
||
assert!(text.is_none());
|
||
assert_eq!(calls.len(), 1);
|
||
assert_eq!(calls[0].name, "search");
|
||
assert_eq!(finish, FinishReason::ToolUse);
|
||
}
|
||
|
||
#[test]
|
||
fn test_assistant_tool_call_empty_id_gets_generated() {
|
||
let tc = IronToolCall {
|
||
id: "".to_string(),
|
||
name: "search".to_string(),
|
||
arguments: serde_json::json!({"query": "test"}),
|
||
};
|
||
let messages = vec![ChatMessage::assistant_with_tool_calls(None, vec![tc])];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
|
||
match &history[0] {
|
||
RigMessage::Assistant { content, .. } => {
|
||
let tool_call = content.iter().find_map(|c| match c {
|
||
AssistantContent::ToolCall(tc) => Some(tc),
|
||
_ => None,
|
||
});
|
||
let tc = tool_call.expect("should have a tool call");
|
||
assert!(!tc.id.is_empty(), "tool call id must not be empty");
|
||
assert!(
|
||
tc.id.starts_with("generated_tool_call_"),
|
||
"empty id should be replaced with generated id, got: {}",
|
||
tc.id
|
||
);
|
||
assert_eq!(tc.call_id.as_deref(), Some(tc.id.as_str()));
|
||
}
|
||
other => panic!("Expected Assistant message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_assistant_tool_call_whitespace_id_gets_generated() {
|
||
let tc = IronToolCall {
|
||
id: " ".to_string(),
|
||
name: "search".to_string(),
|
||
arguments: serde_json::json!({"query": "test"}),
|
||
};
|
||
let messages = vec![ChatMessage::assistant_with_tool_calls(None, vec![tc])];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
|
||
match &history[0] {
|
||
RigMessage::Assistant { content, .. } => {
|
||
let tool_call = content.iter().find_map(|c| match c {
|
||
AssistantContent::ToolCall(tc) => Some(tc),
|
||
_ => None,
|
||
});
|
||
let tc = tool_call.expect("should have a tool call");
|
||
assert!(
|
||
tc.id.starts_with("generated_tool_call_"),
|
||
"whitespace-only id should be replaced, got: {:?}",
|
||
tc.id
|
||
);
|
||
}
|
||
other => panic!("Expected Assistant message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn test_assistant_and_tool_result_missing_ids_share_generated_id() {
|
||
// Simulate: assistant emits a tool call with empty id, then tool
|
||
// result arrives without an id. Both should get deterministic
|
||
// generated ids that match (based on their position in history).
|
||
let tc = IronToolCall {
|
||
id: "".to_string(),
|
||
name: "search".to_string(),
|
||
arguments: serde_json::json!({"query": "test"}),
|
||
};
|
||
let assistant_msg = ChatMessage::assistant_with_tool_calls(None, vec![tc]);
|
||
let tool_result_msg = ChatMessage {
|
||
role: crate::llm::Role::Tool,
|
||
content: "search results here".to_string(),
|
||
content_parts: Vec::new(),
|
||
tool_call_id: None,
|
||
name: Some("search".to_string()),
|
||
tool_calls: None,
|
||
};
|
||
let messages = vec![assistant_msg, tool_result_msg];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
|
||
// Extract the generated call_id from the assistant tool call
|
||
let assistant_call_id = match &history[0] {
|
||
RigMessage::Assistant { content, .. } => {
|
||
let tc = content.iter().find_map(|c| match c {
|
||
AssistantContent::ToolCall(tc) => Some(tc),
|
||
_ => None,
|
||
});
|
||
tc.expect("should have tool call").id.clone()
|
||
}
|
||
other => panic!("Expected Assistant message, got: {:?}", other),
|
||
};
|
||
|
||
// Extract the generated call_id from the tool result
|
||
let tool_result_call_id = match &history[1] {
|
||
RigMessage::User { content } => match content.first() {
|
||
UserContent::ToolResult(r) => r
|
||
.call_id
|
||
.clone()
|
||
.expect("tool result call_id must be present"),
|
||
other => panic!("Expected ToolResult, got: {:?}", other),
|
||
},
|
||
other => panic!("Expected User message, got: {:?}", other),
|
||
};
|
||
|
||
assert!(
|
||
!assistant_call_id.is_empty(),
|
||
"assistant call_id must not be empty"
|
||
);
|
||
assert!(
|
||
!tool_result_call_id.is_empty(),
|
||
"tool result call_id must not be empty"
|
||
);
|
||
|
||
// NOTE: With the current seed-based generation, these IDs will differ
|
||
// because the assistant tool call uses seed=0 (history.len() at that
|
||
// point) and the tool result uses seed=1 (history.len() after the
|
||
// assistant message was pushed). This documents the current behavior.
|
||
// A future improvement could thread the assistant's generated ID into
|
||
// the tool result for exact matching.
|
||
assert_ne!(
|
||
assistant_call_id, tool_result_call_id,
|
||
"Current impl generates different IDs for assistant call and tool result \
|
||
because seeds differ; this documents the known limitation"
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn test_saturate_u32() {
|
||
assert_eq!(saturate_u32(100), 100);
|
||
assert_eq!(saturate_u32(u64::MAX), u32::MAX);
|
||
assert_eq!(saturate_u32(u32::MAX as u64), u32::MAX);
|
||
}
|
||
|
||
// -- normalize_tool_name tests --
|
||
|
||
#[test]
|
||
fn test_normalize_tool_name_exact_match() {
|
||
let known = HashSet::from(["echo".to_string(), "list_jobs".to_string()]);
|
||
assert_eq!(normalize_tool_name("echo", &known), "echo");
|
||
}
|
||
|
||
#[test]
|
||
fn test_normalize_tool_name_proxy_prefix_match() {
|
||
let known = HashSet::from(["echo".to_string(), "list_jobs".to_string()]);
|
||
assert_eq!(normalize_tool_name("proxy_echo", &known), "echo");
|
||
}
|
||
|
||
#[test]
|
||
fn test_normalize_tool_name_proxy_prefix_no_match_kept() {
|
||
let known = HashSet::from(["echo".to_string(), "list_jobs".to_string()]);
|
||
assert_eq!(
|
||
normalize_tool_name("proxy_unknown", &known),
|
||
"proxy_unknown"
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn test_normalize_tool_name_unknown_passthrough() {
|
||
let known = HashSet::from(["echo".to_string()]);
|
||
assert_eq!(normalize_tool_name("other_tool", &known), "other_tool");
|
||
}
|
||
|
||
#[test]
|
||
fn test_build_rig_request_injects_cache_control_short() {
|
||
let req = build_rig_request(
|
||
Some("You are helpful.".to_string()),
|
||
vec![RigMessage::user("Hello")],
|
||
Vec::new(),
|
||
None,
|
||
None,
|
||
None,
|
||
CacheRetention::Short,
|
||
)
|
||
.unwrap();
|
||
|
||
let params = req
|
||
.additional_params
|
||
.expect("should have additional_params for Short retention");
|
||
assert_eq!(params["cache_control"]["type"], "ephemeral");
|
||
assert!(
|
||
params["cache_control"].get("ttl").is_none(),
|
||
"Short retention should not include ttl"
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn test_build_rig_request_injects_cache_control_long() {
|
||
let req = build_rig_request(
|
||
Some("You are helpful.".to_string()),
|
||
vec![RigMessage::user("Hello")],
|
||
Vec::new(),
|
||
None,
|
||
None,
|
||
None,
|
||
CacheRetention::Long,
|
||
)
|
||
.unwrap();
|
||
|
||
let params = req
|
||
.additional_params
|
||
.expect("should have additional_params for Long retention");
|
||
assert_eq!(params["cache_control"]["type"], "ephemeral");
|
||
assert_eq!(params["cache_control"]["ttl"], "1h");
|
||
}
|
||
|
||
#[test]
|
||
fn test_build_rig_request_no_cache_control_when_none() {
|
||
let req = build_rig_request(
|
||
Some("You are helpful.".to_string()),
|
||
vec![RigMessage::user("Hello")],
|
||
Vec::new(),
|
||
None,
|
||
None,
|
||
None,
|
||
CacheRetention::None,
|
||
)
|
||
.unwrap();
|
||
|
||
assert!(
|
||
req.additional_params.is_none(),
|
||
"additional_params should be None when cache is disabled"
|
||
);
|
||
}
|
||
|
||
/// Verify that the multiplier match arms in `RigAdapter::cache_write_multiplier`
|
||
/// produce the expected values. We use a standalone helper because constructing
|
||
/// a real `RigAdapter` requires a rig `Model` (which needs network/provider setup).
|
||
/// The helper mirrors the same match expression — if the impl drifts, the
|
||
/// `test_build_rig_request_*` tests will still catch regressions end-to-end.
|
||
#[test]
|
||
fn test_cache_write_multiplier_values() {
|
||
use rust_decimal::Decimal;
|
||
// None → 1.0× (no surcharge)
|
||
assert_eq!(
|
||
cache_write_multiplier_for(CacheRetention::None),
|
||
Decimal::ONE
|
||
);
|
||
// Short → 1.25× (25% surcharge)
|
||
assert_eq!(
|
||
cache_write_multiplier_for(CacheRetention::Short),
|
||
Decimal::new(125, 2)
|
||
);
|
||
// Long → 2.0× (100% surcharge)
|
||
assert_eq!(
|
||
cache_write_multiplier_for(CacheRetention::Long),
|
||
Decimal::TWO
|
||
);
|
||
}
|
||
|
||
fn cache_write_multiplier_for(retention: CacheRetention) -> rust_decimal::Decimal {
|
||
match retention {
|
||
CacheRetention::None => rust_decimal::Decimal::ONE,
|
||
CacheRetention::Short => rust_decimal::Decimal::new(125, 2),
|
||
CacheRetention::Long => rust_decimal::Decimal::TWO,
|
||
}
|
||
}
|
||
|
||
// -- supports_prompt_cache tests --
|
||
|
||
#[test]
|
||
fn test_supports_prompt_cache_supported_models() {
|
||
// All Claude 3+ models per Anthropic docs
|
||
assert!(supports_prompt_cache("claude-opus-4-6"));
|
||
assert!(supports_prompt_cache("claude-sonnet-4-6"));
|
||
assert!(supports_prompt_cache("claude-sonnet-4"));
|
||
assert!(supports_prompt_cache("claude-haiku-4-5"));
|
||
assert!(supports_prompt_cache("claude-3-5-sonnet-20241022"));
|
||
assert!(supports_prompt_cache("claude-haiku-3"));
|
||
assert!(supports_prompt_cache("Claude-Opus-4-5")); // case-insensitive
|
||
assert!(supports_prompt_cache("anthropic/claude-sonnet-4-6")); // provider prefix
|
||
}
|
||
|
||
#[test]
|
||
fn test_supports_prompt_cache_unsupported_models() {
|
||
// Legacy Claude models that predate caching
|
||
assert!(!supports_prompt_cache("claude-2"));
|
||
assert!(!supports_prompt_cache("claude-2.1"));
|
||
assert!(!supports_prompt_cache("claude-instant-1.2"));
|
||
// Non-Claude models
|
||
assert!(!supports_prompt_cache("gpt-4o"));
|
||
assert!(!supports_prompt_cache("llama3"));
|
||
}
|
||
|
||
#[test]
|
||
fn test_with_unsupported_params_populates_set() {
|
||
use rig::client::CompletionClient;
|
||
use rig::providers::openai;
|
||
|
||
let client: openai::Client = openai::Client::builder()
|
||
.api_key("test-key")
|
||
.base_url("http://localhost:0")
|
||
.build()
|
||
.unwrap();
|
||
let client = client.completions_api();
|
||
let model = client.completion_model("test-model");
|
||
let adapter = RigAdapter::new(model, "test-model")
|
||
.with_unsupported_params(vec!["temperature".to_string()]);
|
||
|
||
assert!(adapter.unsupported_params.contains("temperature"));
|
||
assert!(!adapter.unsupported_params.contains("max_tokens"));
|
||
}
|
||
|
||
#[test]
|
||
fn test_strip_unsupported_completion_params() {
|
||
use rig::client::CompletionClient;
|
||
use rig::providers::openai;
|
||
|
||
let client: openai::Client = openai::Client::builder()
|
||
.api_key("test-key")
|
||
.base_url("http://localhost:0")
|
||
.build()
|
||
.unwrap();
|
||
let client = client.completions_api();
|
||
let model = client.completion_model("test-model");
|
||
let adapter = RigAdapter::new(model, "test-model").with_unsupported_params(vec![
|
||
"temperature".to_string(),
|
||
"stop_sequences".to_string(),
|
||
]);
|
||
|
||
let mut req = CompletionRequest::new(vec![ChatMessage::user("hi")]);
|
||
req.temperature = Some(0.7);
|
||
req.max_tokens = Some(100);
|
||
req.stop_sequences = Some(vec!["STOP".to_string()]);
|
||
|
||
adapter.strip_unsupported_completion_params(&mut req);
|
||
|
||
assert!(req.temperature.is_none(), "temperature should be stripped");
|
||
assert_eq!(req.max_tokens, Some(100), "max_tokens should be preserved");
|
||
assert!(
|
||
req.stop_sequences.is_none(),
|
||
"stop_sequences should be stripped"
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn test_strip_unsupported_tool_params() {
|
||
use rig::client::CompletionClient;
|
||
use rig::providers::openai;
|
||
|
||
let client: openai::Client = openai::Client::builder()
|
||
.api_key("test-key")
|
||
.base_url("http://localhost:0")
|
||
.build()
|
||
.unwrap();
|
||
let client = client.completions_api();
|
||
let model = client.completion_model("test-model");
|
||
let adapter = RigAdapter::new(model, "test-model")
|
||
.with_unsupported_params(vec!["temperature".to_string(), "max_tokens".to_string()]);
|
||
|
||
let mut req = ToolCompletionRequest::new(vec![ChatMessage::user("hi")], vec![]);
|
||
req.temperature = Some(0.5);
|
||
req.max_tokens = Some(200);
|
||
|
||
adapter.strip_unsupported_tool_params(&mut req);
|
||
|
||
assert!(req.temperature.is_none(), "temperature should be stripped");
|
||
assert!(req.max_tokens.is_none(), "max_tokens should be stripped");
|
||
}
|
||
|
||
#[test]
|
||
fn test_unsupported_params_empty_by_default() {
|
||
use rig::client::CompletionClient;
|
||
use rig::providers::openai;
|
||
|
||
let client: openai::Client = openai::Client::builder()
|
||
.api_key("test-key")
|
||
.base_url("http://localhost:0")
|
||
.build()
|
||
.unwrap();
|
||
let client = client.completions_api();
|
||
let model = client.completion_model("test-model");
|
||
let adapter = RigAdapter::new(model, "test-model");
|
||
|
||
assert!(adapter.unsupported_params.is_empty());
|
||
}
|
||
|
||
/// Regression test: consecutive tool_result messages from parallel tool
|
||
/// execution must be merged into a single User message with multiple
|
||
/// ToolResult content items. Without merging, APIs like Anthropic reject
|
||
/// the request due to consecutive User messages.
|
||
#[test]
|
||
fn test_consecutive_tool_results_merged_into_single_user_message() {
|
||
let tc1 = IronToolCall {
|
||
id: "call_a".to_string(),
|
||
name: "search".to_string(),
|
||
arguments: serde_json::json!({"q": "rust"}),
|
||
};
|
||
let tc2 = IronToolCall {
|
||
id: "call_b".to_string(),
|
||
name: "fetch".to_string(),
|
||
arguments: serde_json::json!({"url": "https://example.com"}),
|
||
};
|
||
let assistant = ChatMessage::assistant_with_tool_calls(None, vec![tc1, tc2]);
|
||
let result_a = ChatMessage::tool_result("call_a", "search", "search results");
|
||
let result_b = ChatMessage::tool_result("call_b", "fetch", "fetch results");
|
||
|
||
let messages = vec![assistant, result_a, result_b];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
|
||
// Should be: 1 assistant + 1 merged user (not 1 assistant + 2 users)
|
||
assert_eq!(
|
||
history.len(),
|
||
2,
|
||
"Expected 2 messages (assistant + merged user), got {}",
|
||
history.len()
|
||
);
|
||
|
||
// The second message should contain both tool results
|
||
match &history[1] {
|
||
RigMessage::User { content } => {
|
||
assert_eq!(
|
||
content.len(),
|
||
2,
|
||
"Expected 2 tool results in merged user message, got {}",
|
||
content.len()
|
||
);
|
||
for item in content.iter() {
|
||
assert!(
|
||
matches!(item, UserContent::ToolResult(_)),
|
||
"Expected ToolResult content"
|
||
);
|
||
}
|
||
}
|
||
other => panic!("Expected User message, got: {:?}", other),
|
||
}
|
||
}
|
||
|
||
/// Verify that a tool_result after a non-tool User message is NOT merged.
|
||
#[test]
|
||
fn test_tool_result_after_user_text_not_merged() {
|
||
let user_msg = ChatMessage::user("hello");
|
||
let tool_msg = ChatMessage::tool_result("call_1", "search", "results");
|
||
|
||
let messages = vec![user_msg, tool_msg];
|
||
let (_preamble, history) = convert_messages(&messages);
|
||
|
||
// Should be 2 separate User messages (text user + tool result user)
|
||
assert_eq!(history.len(), 2);
|
||
}
|
||
}
|